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Carbon nanotube-paper composite-capacitive sensor for respiratory monitoring
Recent COVID-19 pandemic highlights the importance of monitoring and prediction of acute respiratory illness. Few options are available for convenient respiratory monitoring in both hospital and community settings. This paper presents a novel respiratory monitoring sensor made of carbon nanotube-paper composites (CPC). A CPC capacitive sensor fabricated with tensional fracture consists of numerous cellulose fibers coated with carbon nanotubes (CNTs). The high aspect ratio structure significantly enhances the capacitive sensitivity due to the high electric field.
Various carbon nanotube–paper composites (CPCs) have been studied to measure relative humidity. This study presents a tissue paper-based CPC coated with polyacrylic acid (PAA) for sensing humidity and surface moisture. When the CPC is exposed to humidity, its electrical resistance changes due to its electrostatic interaction with water molecules and the swelling of cellulose fibers and PAA. The enhancement of sensor response due to the swelling of CPCs coated with PAA, acid, and Nafion is studied in terms of resistance change.
The full potential of carbon nanotubes (CNTs), one of the most widely used nanomaterials to date, still remains to be realized, and the dispersion of CNTs is one of the main challenging tasks for many practical applications. Lignin, one of the most abundant renewable polymers, has recently been investigated as a potential dispersant to prepare CNT suspensions. The present study provides a benchmark of the effectiveness of lignin in dispersing CNTs compared to typical petrochemical surfactants.
Nanostructured composites built with microporous cellulose fibers and carbon nanotubes (CNTs) have potential impacts in the fields of energy storage, sensors, and flexible electronics. Few results have been shown for high mechanoelectrical sensitivity of CNT-paper composite because of numerous current paths in the network. Here, CNT-paper-based nanostructured composite sensors whose sensitivities are generated by controlled tensile fracture of the composite are presented. Under uniaxial load, the cellulose fibers in the paper experience straightening, stiffening, and fracture.
Human–machine interface requires various sensors for communication, manufacturing and environmental control, and health and safety monitoring. Capacitive sensors have been used to detect touch, distance, geometry, electric property, and environmental parameters. However, highly sensitive proximity detection with a small form factor has always been a challenge. This paper presents a capacitive sensor composed of a nanostructured electrode array for contact and noncontact detection. In the sensor configuration, the nanostructured electrode is made of high aspect ratio cellulose fibers embedded with carbon nanotubes. The complementary electrode is designed to be smaller in surface area for high sensitivity. Based on the analysis, the unique sensing mechanism is shown to enhance the proximity sensitivity for target detection. A pair of asymmetrically designed electrodes are characterized and compared with the traditional symmetric electrodes for proximity and contact detection of human hands. The sensor performance is also characterized for detecting water mass in glass and metal cups. In the end, a smart pad that can recognize human gestures, gait, and water mass with unprecedented sensitivity is demonstrated.
The uniqueness of eyes, facial geometry, and gaze direction makes eye tracking a very challenging technological pursuit. Although camera-based eye-tracking systems are popular, the obtrusiveness of their bulky equipment along with their high computational cost and power consumption is considered problematic for wearable applications. Noncontact gaze monitoring using capacitive sensing technique has been attempted but failed due to low sensitivity and parasitic capacitance. Here, we study the interaction between a novel capacitive sensor and eye movement for wearable eye-tracking. The capacitive sensors are made of a pair of asymmetric electrodes; one comprising carbon nanotube-paper composite fibers (CPC) and the other being a rectangular metal electrode. The interaction between the asymmetric sensor and a spherical object mimicking an eyeball is analyzed numerically. Using a face simulator, both single- and differential capacitive measurements are characterized with respect to proximity, geometry, and human body charge. Using a prototype eye tracker, multiple sensor locations are studied to determine the optimal configurations. The capacitive responses to vertical and horizontal gaze directions are analyzed in comparison to those of a commercial eye tracking system. The performance is demonstrated for sensitive eye-movement tracking, closed-eye monitoring, and human-machine interface. This research has important implications for the development of capacitive, wearable eye trackers, which can facilitate fields of human-machine interface, cognitive monitoring, neuroscience research, and rehabilitation.